Requirements

Expected technologies

Python

SQL

SAS

R

Our requirements

• Bachelor’s or Master’s degree in Data Science, Statistics, Finance, Economics, or related field.
• 5+ years of experience in fraud analytics, financial crime modeling, or data science roles.
• Strong command of statistical modeling, forecasting, and cost-benefit analysis.
• Proficiency in Python and SQL (required); SAS and R (preferred).
• Experience working with cross-functional teams and external vendors.
• Excellent communication skills with the ability to present complex findings clearly.
• Ability to work independently in a fast-paced, ambiguous environment.

Optional

• Experience in banking or financial services.
• Familiarity with fraud prevention infrastructure and regulatory frameworks.
• Exposure to vendor governance and contract evaluation processes.

Your responsibilities

• Analyze fraud trends across First Party, Third Party, Account Takeover, and Account Origination scenarios using statistical and machine learning techniques.
• Build predictive models and cost-benefit frameworks to assess fraud mitigation tools and strategies.
• Conduct post-implementation analytics to validate the effectiveness of fraud controls.
• Collaborate with vendor management teams to assess tool performance, reconcile invoices, and forecast budget impacts.
• Prepare executive-level dashboards and reports to support strategic decision-making.
• Ensure model governance and compliance with internal and regulatory standards.
• Use advanced data tools (Python, R, SAS, SQL) to conduct exploratory analysis and synthesize insights from multiple sources.